AWS RDS Cost Calculator
Estimate RDS-style managed database cost with a simple model: instance hours + storage + backup storage + I/O requests using hours/day x days/month, then compare baseline vs peak I/O.
Inputs
Instances
Price ($ / hour / instance)
Hours/day
Use 24 for always-on DBs.
Days/month
Use 30.4 for an average month.
Monthly hours: 730
Storage (GB-month)
Approx 0.2 TB-month.
Starting storage (GB)
Monthly growth (%)
Months in period
Est 186 GB-month avg.
Storage price ($ / GB-month)
Backup storage (GB-month)
Backup ratio 100%.
Backup ratio (%)
Current ratio 100% of storage.
Est 200 GB backups.
Backup price ($ / GB-month)
I/O requests (per month)
Avg 1,903.6 IOPS.
Avg IOPS
Use average read + write IOPS.
Est 5,253,120,000 I/O requests/month.
I/O price ($ / 1M requests)
Scenario presets
Results
Estimated monthly total
$1,187.92
Compute
$145.92
DB storage
$23.00
Backups
$19.00
I/O requests
$1,000.00
I/O requests (per month)
5,000,000,000
Billable hours (fleet)
730 hr
How to get your inputs
- Compute: instance-hours from billing (hours/day x days/month) or average serverless capacity.
- Storage: average allocated or used GB-month and expected growth.
- Backups: retention x daily change rate to estimate backup GB-month.
- I/O: use engine metrics or billing for I/O request volume.
Result interpretation
- If backups are a large share, review retention and snapshot lifecycle policies.
- If I/O is dominant, evaluate storage type and workload patterns before scaling instance size.
Common mistakes
- Ignoring backup storage growth and retention creep.
- Using allocated storage as a constant without growth assumptions.
- Forgetting I/O pricing for engines that charge per request.
Advanced inputs to capture
- Model instance hours by size and uptime schedule.
- Add storage GB-month plus provisioned IOPS if applicable.
- Include backup and snapshot retention driven by churn.
- Account for Multi-AZ or read replica overhead.
Scenario planning
| Scenario | Instances | Storage | Backups | I/O |
|---|---|---|---|---|
| Baseline | Expected | Average | Retention plan | Normal workload |
| Peak | Same or +1 | Growth | Higher churn | Batch/backfill |
Validate after changes
- Compare instance-hours, storage, backups, and I/O to actual RDS line items.
- Re-check during batch jobs or backfills when churn spikes.
Next steps
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Example scenario
- 1 instance at $0.20/hour running 24 hours/day for 30 days, 200GB storage, 200GB backups, and 5B I/O requests/month.
- Peak 220% scenario highlights batch workloads and backfills.
Included
- Compute from instances x hours/day x days/month x $/hour.
- Storage from GB-month x $/GB-month.
- Backup storage from GB-month x $/GB-month.
- I/O requests from monthly I/O volume x $ per 1M requests.
- Optional storage growth, backup ratio, and IOPS estimators.
- Baseline vs peak scenario table for I/O spikes.
Not included
- Network/data transfer, monitoring/logs, licensing, taxes, and feature add-ons.
- Free tiers, tiered steps, and per-engine differences unless you reflect them in pricing inputs.
How we calculate
- Compute cost = instances x (hours/day x days/month) x $ per hour.
- Storage cost = GB-month x $ per GB-month.
- Backup cost = backup GB-month x $ per GB-month.
- I/O cost = (I/O requests per month / 1,000,000) x $ per 1M I/O requests.
- Total = compute + storage + backups + I/O (excluding transfer and add-ons).
FAQ
Why do I need to enter pricing?
RDS pricing varies by engine, region, storage type, and discounts. Use your effective rates for accurate estimates.
Does this include Multi-AZ replicas or read replicas?
Not directly. Model additional instances and storage as separate line items (or increase instance count and backup/storage inputs).
What should I use for I/O requests?
Use monitoring/engine metrics or estimate from workload. If you don't have I/O pricing in your plan, set it to $0 to exclude.
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Disclaimer
Educational use only. Not legal, financial, or professional advice. Results are estimates based on the inputs and assumptions shown on this page. Verify pricing and limits with your providers and documentation.
Last updated: 2026-02-07